Taking a hybrid approach gives some key advantages over purely machine learning systems.
A machine learning conversational system has no consistent personality, because the dialog answers are all amalgamated text fragments from different sources. From a business point of view, this misses the opportunity to position the company through identifiable brand values.
But the issue of a consistent personality is dwarfed by the problem of semantics. In a linguistic-based conversational system, enterprises can ensure that questions with the same meaning receive the same answer. A machine learning conversational system however might well fail to recognize similar questions phrased in different ways, even within the same conversation.
Teneo’s hybrid approach offers a unique simplifying benefit. The rules and the intelligence architecture behind the conversations can be directly integrated and maintained alongside each other in the same visual interface. This ensures that conversational AI applications properly understand the context of the conversation – every time.
Before Teneo, building conversational AI applications using traditional natural language methods was difficult, resource intensive and frequently prohibitively expensive. With Teneo, enterprises can rapidly develop business-relevant AI applications that can make a difference to the customer experience and the bottom line.